How AI is Transforming the "No Hardware" Investment Mindset
In venture capital, we've long held a bias toward software startups, which is understandable given their scalability, capital efficiency, and relatively lower risk.
But with AI, it's becoming more compelling to evaluate opportunities that might otherwise have been a quick pass simply because they involve hardware.
AI is opening up new possibilities for what physical products can do. Devices and machines can increasingly learn, adapt, make decisions, and improve through software updates. When hardware and software are tightly integrated, the complexity of building both can also create meaningful barriers to entry.
The result is a growing class of companies that don't fit neatly into the traditional software-versus-hardware divide and deserve a closer look from investors who historically wouldn't have considered them.
The Hardware Investment Hurdle
There's a reason investors have been cautious about hardware.
Hardware companies can require significant upfront capital for R&D, prototyping, manufacturing, and inventory. Development cycles tend to be longer, and mistakes are more expensive to correct once a product has been built and deployed.
Scaling brings another set of challenges: managing supply chains, sourcing components, financing inventory, and manufacturing and distributing physical products. Margins can also be lower than those of pure software businesses.
Put together, these characteristics have made traditional hardware a difficult fit for the venture model.
Rethinking Hardware Investment in the Age of AI
AI can make physical products more capable and dynamic than traditional hardware.
By integrating machine learning and real-time decision-making, hardware can increasingly learn, adapt, and improve through software updates. That can extend the functionality of a product while creating opportunities for personalization, predictive maintenance, and continuous performance improvements.
AI can also change the business model.
Rather than relying entirely on one-time hardware sales, companies can pair physical products with software subscriptions, service contracts, or other recurring revenue streams. For investors, that can create more attractive economics and reduce dependence on the hardware replacement cycle.
At the same time, we're seeing significant venture capital flow into companies where hardware is central to the technology:
Groq, which is developing specialized chips for AI inference, recently raised a $640 million Series D led by BlackRock.
Anduril raised $1.5 billion, co-led by Founders Fund and Sands Capital, to continue developing autonomous systems for military use.
Bee, a wearable AI assistant that listens, learns, takes notes, and provides reminders, raised a $7 million Seed round led by Exor.
These are very different companies, but they point to the same broader shift: AI is expanding what hardware can do and changing how we should think about the businesses built around it.
What Makes AI Hardware Venture-Backable?
Of course, adding AI doesn't suddenly make every hardware company a venture investment. The traditional concerns around capital intensity, manufacturing, margins, and distribution still matter.
But those risks need to be weighed against what the technology makes possible. A company that delivers a significant technological leap, creates meaningful barriers to entry, or opens a sufficiently large market may justify economics that would have previously caused investors to pass.
Hardware companies that can generate recurring revenue independent of the hardware replacement cycle become particularly interesting. Software subscriptions, service contracts, and other ongoing revenue models can create steadier cash flow, deepen customer relationships, and improve margins over time.
So the question isn't simply whether a company sells hardware. It's whether the business can create enough value to justify the additional capital and complexity that come with building it.
Industries at the Forefront of AI-Powered Hardware
Industrial Automation. AI-enabled equipment can improve manufacturing and logistics through automation, predictive maintenance, inspection, and more intelligent operations.
Aerospace and Defense. AI integration in drones, satellites, and military systems enables increasingly sophisticated autonomous operations, real-time analysis, and mission-critical decision-making.
Transportation. AI can enable autonomous vehicles, improve route planning, optimize fleet performance, and enhance safety across the movement of people and goods.
Healthcare. AI-enhanced medical devices can improve diagnostics, monitoring, and personalized treatment.
Consumer Electronics. AI in phones, wearables, and other devices can enable more personalized, adaptive, and intuitive interactions.
Across these categories, the common thread is intelligence moving beyond the screen and into the physical products and systems around us.
Key Hardware Investment Trends to Watch
Reshoring Manufacturing
Reshoring is gaining momentum as the U.S. prioritizes strengthening its industrial base and global competitiveness.
Building more domestically will require investment not only in manufacturing facilities but also in the technologies that make those facilities more productive. Automation, predictive maintenance, inspection, and supply-chain optimization will become increasingly important as manufacturers look to increase efficiency and reliability.
That should create opportunities for technology companies serving the next generation of American manufacturing.
A Focus on AI Infrastructure
As AI becomes more important across industries, investment in the physical technologies required to support it should grow as well.
Advanced processors, high-precision sensors, data storage solutions, and other technologies supporting AI applications will be increasingly important to delivering performance at scale.
AI won't create opportunities only at the application layer. It will also drive demand for the underlying hardware that makes those applications possible.
Green Hardware
Energy efficiency is another area I'm watching.
Energy-efficient processors, smarter power-management systems, and materials that improve thermal performance can reduce both energy consumption and operating costs.
As computing requirements increase, technologies that can deliver greater performance with lower energy requirements could become increasingly valuable.
Beyond "No Hardware"
The preference for software was built around real economic advantages. Those advantages haven't disappeared, and neither have the challenges associated with building physical products.
But a strict “no hardware” rule is becoming harder to justify.
AI is expanding what physical systems can do, while software and new business models are changing how value can be created around them. That doesn't mean software investors suddenly need to become traditional hardware investors. It means the distinction between the two is becoming less useful.
As hardware and software become more deeply integrated, more companies are going to land somewhere in the middle. Some will be hardware businesses with AI bolted on. Others will use AI to make physical products that learn, adapt, and improve after they're deployed.
For software investors excited about AI, those companies may be worth a closer look.
-Kiswana